Product improvement based on online reviews from product designer's perspective

4th International Conference on Applied Materials and Manufacturing Technology

材料科学;机械制造

Li, Shugang^1 ; Kong, Jiali^1

School of Management, Shanghai University, Shanghai

200444, China^1

关键词: Consumer shopping;    Emotional classification;    Emotional vectors;    Emotional words;    Joint analysis;    Online shopping;    Product designers;    Product improvement;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/423/1/012114/pdf
DOI  :  10.1088/1757-899X/423/1/012114

学科分类：材料科学（综合）

来源: IOP

【 摘 要 】

With the popularity of online shopping, the number of online reviews has greatly increased. Online reviews have become a major factor influencing consumer shopping behaviour and have become one of the references for product designers to improve their products. It is difficult for product designers to obtain useful information for improving products from mass reviews. From the perspective of product design, the article establishes a product improvement model. First, in order to filter noise effectively, this paper uses word2vec and cosine distance to convert words into emotional word vectors innovatively. Then the emotional vector is used as the input of the GRU(Gated recurrent units) neural network for emotional classification. Finally, we propose a product improvement strategy from a product designer's perspective combined with a joint analysis model. In addition, we conducted case studies using new methods in Disneyland's online reviews. Case studies show the effectiveness of the method.